bcraapi is a Python wrapper for BCRA APIs provided by Banco Central de la República Argentina itself. It makes use of requests and pandas and returns the data in a pandas DataFrame.
The BCRA API does not require tokens or registration, so do not hesitate to use it.
pip install bcraapi
You will be able to access to resources related to exchange rate information published by the BCRA.
You will be able to consult reported, lost, stolen or adulterated checks. The information available here is provided by the financial entities operating in the country and is published without alterations.
You will be able to access resources related to the main variables information published by the BCRA.
You will be able to access resources related to the main variables information published by the BCRA.
Method to obtain the list of all the banking entities in the country with their respective entity code.
from bcraapi import cheques
df = cheques.entidades()DataFrame with the list of all the banking entities in the country with their respective entity code.
Method to know if a check from a certain entity is registered as reported or not.
from bcraapi import cheques
df = cheques.denunciados(codigo_entidad=11, numero_cheque=20377516)| Parameter | Type | Description |
|---|---|---|
codigo_entidad |
int |
ID of the financial entity. It can be queried via entidades(). |
numero_cheque |
int |
Corresponds to the check number to be consulted. |
DataFrame with the result if a check is registered as reported or not.
Method to obtain the list of all variables published by the BCRA.
from bcraapi import estadisticas
df = estadisticas.principales_variables()DataFrame with the variables published by the BCRA.
Method to obtain the values for the variable and date range indicated.
from bcraapi import estadisticas
df = estadisticas.datos_variable(id_variable=1, desde="2024-02-01", hasta="2024-02-05")| Parameter | Type | Description |
|---|---|---|
id_variable |
int |
ID of the desired variable. You can view all available ids and descriptions with the principales_variables() method. |
desde |
str |
The start date of the range to be queried, it must be in the format YYYY-MM-DD. |
hasta |
str |
The end date of the range to be queried, it must be in the format YYYY-MM-DD. |
DataFrame with the values for the selected variable and date range.
Method to obtain the list of all ISO currencies in force, with their respective denominations. denomination.
from bcraapi import estadisticascambiarias
df = estadisticascambiarias.maestros_divisas()DataFrame with the list of currencies of the BCRA.
Method to obtain the list of all current foreign exchange rates published by the BCRA for a given date (yyyy-MM-dd). BCRA for a given date. If no date is entered, the last existing quote will be returned. the last existing quotation will be returned.
from bcraapi import estadisticascambiarias
df = estadisticascambiarias.cotizaciones(fecha="2024-06-12")| Parameter | Type | Description |
|---|---|---|
fecha |
str |
Date of the data to be consulted, it must have the format YYYY-MM-DD. |
DataFrame with the values for the selected date.
Method to obtain the price evolution of a currency (ISO) in a particular date range. If the date from and date to parameters are not entered, the last existing quote will be returned. the last existing quote will be returned.
from bcraapi import estadisticascambiarias
df = estadisticascambiarias.cotizaciones_moneda(moneda="USD")| Parameter | Type | Description |
|---|---|---|
moneda |
str |
ISO currency. This parameter is required |
fecha_desde |
str |
The start date of the range to be queried, it must be in the format YYYY-MM-DD. |
fecha_hasta |
str |
The end date of the range to be queried, it must be in the format YYYY-MM-DD. |
limit |
int |
Maximum amount to be returned per application. Must be greater than 10 and less than 1000. |
ofset |
int |
Exclude from the answer the first N elements of the contributions to be refunded.. |
Datarame with the evolution of the exchange rate of a currency.
Method to obtain the credit situation, amount of debt, days in arrears and observations corresponding to the last period reported by the entities to the BCRA.
from bcraapi import centraldeudores
df = centraldeudores.deudas(30500010912)| Parameter | Type | Description |
|---|---|---|
identificacion |
str |
Corresponds to CUIT/CUIL/CDI, it must be 11 characters long. |
DataFrame with the credit situation, amount of debt, days in arrears and observations corresponding to the last period reported by the entities to the BCRA.
Method to obtain the credit situation for the last 24 months.
from bcraapi import centraldeudores
df = centraldeudores.deudas_historicas(30500010912)| Parameter | Type | Description |
|---|---|---|
identificacion |
str |
Corresponds to CUIT/CUIL/CDI, it must be 11 characters long. |
DataFrame with the credit situation for the last 24 months.
Method to obtain the rejected checks with their corresponding reasons.
from bcraapi import centraldeudores
df = centraldeudores.cheques_rechazados(30717283186)| Parameter | Type | Description |
|---|---|---|
identificacion |
str |
Corresponds to CUIT/CUIL/CDI, it must be 11 characters long. |
DataFrame with the rejected checks with their corresponding reasons.